Measurement of bone mass and turnover

4 Measurement of bone mass and turnover

NICOLA PEEL RICHARD EASTELL

Current fracture risk in an individual relates to a combination of bone strength and the risk of falling (Melton and Riggs, 1983; Riggs and Melton, 1986; Hui et al, 1988). It is well established that the major determinant of bone strength is bone mass or bone mineral density (BMD), which accounts for approximately 75-85% of its variability (Mazess, 1982). The remaining variability can be explained by factors such as bone architecture that affect the ability to withstand stress. Attempts to predict osteopenia, or low B M D , from life-style factors such as body habitus and smoking history have proved to have low sensitivity and specificity, although a number of risk factors for osteopenia can be identified in large groups of subjects (Spector et al, 1992). Direct estimation of B M D is therefore the most useful measurement to make in determining an individual's current fracture risk. The therapies that can be used for osteoporosis are more effective in prevention than in treatment, and so the most useful information in planning a management strategy would be knowledge of an individual's future fracture risk. This relates to the peak bone mass achieved in early adult life, and the subsequent rate and duration of bone loss. Rates of bone loss can be assessed from serial measurements of BMD, but this takes time. A possible alternative would be the use of biochemical markers of bone turnover to predict the rate of bone loss, or at least to categorize individuals into 'slow', 'average' or 'fast' bone losers, to try to predict those at risk of osteoporosis in the future. Another potential role for the biochemical markers of bone turnover is in predicting and monitoring the response to therapeutic intervention. In this chapter we review the techniques currently available for measuring BMD and bone turnover, and address the use of these techniques in current clinical practice.

ASSESSMENT OF CURRENT F R A C T U R E RISK

Measurement of B M D is the most accurate method available to determine current fracture risk (Riggs et al, 1987; Ross et al, 1988). Figure 1 shows the relationship between BMD and fracture risk, demonstrating that there is an Bailli~re's Clinical Rheumatology--

Vol. 7, No. 3, October 1993 ISBN0-7020-1711-6

479 Copyright9 1993,by Bailli6reTindall All rightsof reproductionin any form reserved

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almost exponential relationship between the two. The importance of this relationship is that, whilst in the individual with normal BMD a small change in BMD has little impact on fracture risk, in the osteopenic individual a small change in BMD results in a large change in fracture risk. Such small changes can result from the use of drugs that are currently available and it is important to be able to monitor these changes in the development of new therapeutic agents as well as in the management of patients with osteoporosis. The optimum site for BMD measurement has been the subject of considerable controversy. Osteoporotic fractures typically occur in bones that are composed of a high proportion of trabecular bone such as the vertebral body, proximal femur and distal radius. These are the sites commonly chosen for measurement of BMD. BMD measurements are site-specific in that BMD of the ultra-distal radius can predict the risk of Colles' fracture better than the risk of vertebral fracture (Eastell et al, 1989), while the BMD of the lumbar spine does not predict the risk of hip fracture as well as the BMD of the femoral neck (Riggs et al, 1981; Cummings et al, 1993). This relationship may be confounded, however, by inaccuracies resulting from the presence of artefacts such as osteophytes, loss of intervertebral joint space, vertebral collapse, aortic calcification or posterior facet joint arthritis within the region of analysis of standard anteroposterior lumbar spine scans (Orwoll et al, 1990; Frye et al, 1992; Ross et al, 1988; Ryan et al, 1992).

MEASUREMENT OF BONE MASS AND TURNOVER

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These artefacts all increase in frequency with age and may limit the use of lumbar spine measurement in an elderly population. The recent introduction of lateral scans of the vertebral bodies which exclude these artefacts attempts to overcome this problem, but until now the precision of lateral measurements has not been good enough to allow improved diagnostic accuracy; at the present time their use has not been validated (Slosman et al, 1990; Uebelhart et al, 1990; Mazess et al, 1991; Rupich et al, 1992). Both the proximal femur and the lumbar spine should be measured in the assessment of osteopenia, as osteoporotic fractures are c o m m o n in these two areas. In practice, due to limited resources, a single measurement site is frequently used. In the majority of situations measurement of one site gives a reasonable indication of overall fracture risk, although the information about a specific site is less clear.

TECHNIQUES USED TO MEASURE BMD A number of factors determine the ideal B M D measurement technique in the management of osteoporosis. It needs to be accurate, to reflect the true bone mass. It needs to be reproducible, both in the short and long term, to enable serial measurements to be made. The measurement technique must be acceptable to the patient and safe in terms of radiation exposure since repeated measurements may be made to monitor therapeutic response. There are several techniques now available which enable the rapid, accurate and precise measurement of B M D at a number of skeletal sites. These have been comprehensively described in several recent reviews (Eastell and Wahner, 1989; Wahner, 1989; Mazess, 1990; Fogelman and Ryan, 1992). They are summarized in Table 1 and described in outline below.

Table 1. Comparison of techniques used to measure bone mineral density. Method SPA DPA DXA

QCT Ultrasound

Site of measurement Distal radius Mid radius Lumbar spine Proximal femur Total body Lumbar spine AP Lumbar spine lateral Proximal femur Total body Axial Appendicular Calcaneus

Average scan Accuracy Precision Radiation dose time (min) (%) (%) (ixSv) 15 15 20-40 20-40 60 5-7 15 4-6 20 10 10 2-5

5-8 5-8 4-8 4-8 8-10 4-8 4-8 4-8 8-10 5-15 5-15 9

1-3 1-3 2 2-4 1-2 < 1.0 2-5 2-3 < 1.0 4-6 1 2-6

0.5-1.0 0.5-1.0 0.1-0.4

20-100 None

SPA. single photon absorptiometry; DPA, dual photon absorptiometry; DXA, dual-energy X-ray absorptiometry; QCT, quantitative computed tomography.

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Single photon absorptiometry (SPA) The technique of SPA involves measurement of the attenuation of a highly collimated beam of monoenergetic radiation derived from a radio-active iodine source through the area of interest. The source is coupled to a radiation detector and the bone mineral content is derived from the attenuation of the radiation by bone in relation to surrounding soft tissue (Cameron and Sorenson, 1963). The limb may be submerged in a water bath or surrounded by a water bag to achieve a constant thickness of soft tissue equivalent around the bone. This limits the range of measurements that can be made to peripheral sites such as the radius and metacarpals. A correction for the fat content of the area being measured is made, as fat attenuates the radiation beam less than water. The method has the advantages of being inexpensive and relatively portable, and it enables measurements to be made at sites of varying cortical-trabecular composition. A variation of this technique is single-energy X-ray absorptiometry. A fore-arm scanner using this method has recently become commercially available (Osteometer) and has the potential advantage over conventional SPA of improved long-term precision due to the stability of the X-ray source.

Dual photon absorptiometry (DPA) In this technique, a dual-energy beam of radiation, derived from a gadolinium source, enables the measurement of BMD at sites inaccessible to SPA. By using two different photon energies (44 and 100 keV) the differences in attenuation coefficients for bone and soft tissue allow the differentiation of bone and soft tissue components and can take account of variations in soft tissue thickness. Thus, measurements can be made of the spine and proximal femur. In addition, measurements of the whole skeleton and soft tissue composition can be made.

Dual-energy X-ray absorptiometry (DXA) In DXA, the gadolinium source of DPA is replaced by an X-ray source. This has the advantage of being more stable than the isotope source and not requiring regular replacement. The X-ray beam may be more highly collimated, allowing better spatial resolution, and hence measurements by DXA are more precise than those by DPA; they are also faster and use a lower radiation dose (Cullum et al, 1989; Mazess et al, 1992). For these reasons, measurements by DXA have largely superseded those of DPA. There are two different approaches to the production of a dual-energy X-ray beam. In one system (used by Hologic) the X-ray tube switches rapidly between high and low voltage settings. This gives a fluctuating voltage output which is calibrated by placing a rotating wheel containing known reference materials in the beam. Thus, within each pixel of the scan, attenuation by the reference materials as well as by the patient is measured. In the other system, used by Lunar, Norland and Sopha scanners, a stable X-ray tube with constant voltage is used. The beam is then passed through a

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illustrates the r e g i o n of i n t e r e s t s e l e c t e d for analysis. T h e results are e x p r e s s e d on the r i g h t as area (cm2), b o n e m i n e r a l c o n t e n t ( B M C ) (g) a n d bone~mineral d e n s i t y ( B M D ) (g/cm 2) for e a c h ve~:tebral b o d y a n d the g l o b a l r e g i o n L 1 - L 4 . T h e g l o b a l B M D is s h o w n o n the g r a p h b e l o w in c o m p a r i s o n to the m a n u f a c t u r e r ' s r e f e r e n c e range. T h e d o t t e d line shows the l o w e r l i m i t of the r e f e r e n c e r a n g e for y o u n g adults. T h e v a l u e s for e a c h r e g i o n are also s h o w n in the t a h l e b e l o w the g r a p h as a p e r c e n t a g e of the v a l u e e x p e c t e d for age, a n d in c o m p a r i s o n to y o u n g n o r m a l s . T and Z scores are also shown. T h e s e r e p r e s e n t the B M D as SD units f r o m the r e f e r e n c e m e a n v a l u e s for y o u n g n o r m a l s a n d a g e - m a t c h e d c o n t r o l s respectively.

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K-edge filter made from cerium or samarium to split the beam predictably into two different energy beams. Because the method of edge detection varies between the different instruments, and there are differences in calibration, the absolute BMD differs by about 10-15%. As in the case of DPA, scans may be made of areas of particular relevance to the management of osteoporosis. Figure 2 shows an example of a D X A scan of the lumbar spine. Recent developments also enable other areas of interest to be examined; for instance, it is possible to measure the bone density in the periprosthetic region following joint replacement (Engh et al, 1992), and the bone mineral content of the hand can be measured, which may enable the early detection of juxta-articular osteopenia in rheumatoid arthritis (Peel et al, 1992). Newer D X A scanners offer the option of a rapid scan mode. Using this option, a scan of the lumbar spine can be performed in as little as 5 s (Buxton et al, 1993). Because of the resulting loss of precision, these scans are not yet applicable to research or routine clinical practice, but they may have a place if screening programmes are to be developed. BMD measured by SPA, DPA and D X A is a planar or two-dimensional measurement, expressed as g/cm 2. These measurements do not, therefore, fully correct for differences in skeletal size and tend to underestimate BMD in smaller individuals. The failure to correct for the third dimension is particularly important in the case of serial measurements in growing children and may also partially account for racial differences in BMD. Using measurements taken directly from the scan, and making some assumptions about bone morphometry, it is possible to make an estimate of volumetric BMD of the vertebrae and femoral neck (Drinkwater et al, 1992; Peel and Eastell, 1992). There is little evidence to support the use of these corrections in routine clinical practice, but in certain situations, such as those suggested above, they may improve diagnostic accuracy.

Quantitative computed tomography (QCT) This X-ray-based technique enables measurement of volumetric BMD and is also able to differentiate between cortical and trabecular bone (Karantanas et al, 1991). Single-energy QCT may be used to measure peripheral and axial sites of the skeleton, but not the proximal femur. The accuracy of these measurements in the axial skeleton is limited owing to the effect of fat within the bone marrow. The accuracy of QCT measurements is improved by the use of a dual-energy system, but at the expense of an increase in the radiation dose and poorer precision.

Ultrasound Ultrasound has been used to measure the bone in osteoporosis (Heaney et al, 1989; McCloskey et al, 1990; Agren et al, 1991; Baran, 1991). The technique may be applied to peripheral sites, most commonly the calcaneus, and involves the passage of a relatively low frequency ultrasound (0.20.6MHz) through the measurement site, where it is detected by a second transducer. Both attenuation of the ultrasound and its velocity relate to the

MEASUREMENT OF BONE MASS AND TURNOVER

485

bone density. The interest in the technique is twofold. First, it does not involve ionizing radiation, making it applicable to certain clinical situations such as the study of bone mass in children and in pregnancy, and, second, it seems likely that measurements using ultrasound may reflect differences in bone architecture. The use of ultrasound is limited to research applications at present, but studies suggest that it may have adequate diagnostic accuracy to be used as a screening tool, or that it may be a useful adjunct to other BMD measurements to give additional information about bone architecture and hence strength. INDICATIONS FOR BMD MEASUREMENT

The indications for measurement of BMD recently proposed by the Scientific Advisory Board of the National Osteoporosis Foundation in the USA are summarized in Table 2 (Johnston et al, 1989). These guidelines were drawn up, taking into account indications for BMD measurement that could be justified from published data. They will undoubtedly be updated as further evidence becomes available to justify the use of BMD measurement in different clinical situations. Table 2. Indications for bone mineral density measurement proposed by the Scientific Advisory

Board to the National Osteoporosis Foundation of the USA. From Johnston et al (1989). Definite indication

Potential indication

Oestrogen deficiency

Monitoring response to therapy for osteoporosis Screening for osteoporosis

Vertebral deformity or radiographic osteopenia Long-term glucocorticoid therapy Asymptomatic primary hyperparathyroidism

Identification of fast bone losers Secondary osteoporosis

The use of BMD measurement in oestrogen deficiency to identify those women who would benefit from the bone-sparing action of hormone replacement therapy is discussed elsewhere in this volume (Chapter 12). Osteopenia cannot be reliably detected from plain radiographs and, when it is suspected from the radiographic appearances by the presence of prominent vertical trabeculae and vertebral body end-plates relative to the surrounding bone, BMD measurement is indicated to evaluate the presence and severity of osteopenia. Similarly, BMD measurement is a useful component of the evaluation of minor vertebral deformities commonly seen on radiographs. These may represent minor fractures, they may be the physiological wedging seen in the thoracic vertebrae, or may result from conditions such as Scheuermann's disease or juvenile epiphysitis. This condition can produce apparent wedging, particularly of thoracic vertebrae, which is not associated with decreased BMD (Peel et al, 1993). The use of BMD measurement in the assessment of patients receiving long-term steroid therapy is, however, less clear-cut. These patients are clearly at risk of rapid bone loss with a consequent increase in their risk of osteoporosis but

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they are usually treated with the minimum dose possible and, as yet, there is no proven prophylaxis or therapy for steroid-induced osteoporosis (see Chapter 10). The detection of osteopenia in patients with asymptomatic primary hyperparathyroidism is important since it is known that surgical treatment of such patients may result in an increase in B M D (Leppla et al, 1982; Eastell et al, 1986a). The most important potential use for B M D measurement is in the monitoring of therapeutic interventions in osteoporosis. The precision of current methods of B M D measurement is such that significant changes in B M D can be detected within 1-2 years. This is important as it appears that a proportion of patients fail to respond to conventional therapies. In addition, because osteoporosis is a condition that is asymptomatic unless a fracture occurs, evidence of efficacy may enhance compliance with treatment. The use of B M D measurements for screening and in secondary osteoporosis are discussed elsewhere in this volume and we will consider the use to measure the rate of bone loss later in this chapter.

A P P R O A C H E S TO DESCRIBING BMD M E A S U R E M E N T S

It is important to present results from BMD measurements in a way that is easy to comprehend, both to the physician and the patient, and that gives as much information as possible without being misleading (Parfitt, 1990). B M D results for D X A measurements may be expressed: (1) as the absolute value, in g/cm2; (2) as a percentage, either in relation to age-matched controls, or in comparison with young adults; (3) as a Z score; or (4) as a percentile. We will discuss the advantages and disadvantages of each of these approaches. The absolute BMD value is probably the most meaningful value in terms of determining current fracture risk, but in order to understand the implication of a result it is necessary to know the relationship between B M D and fracture risk for the measurement site and demographic group in question. It is also difficult to explain'the significance of absolute values to a patient. For this reason, values are commonly expressed as a percentage of the expected value for an age- and sex-matched individual since most people are familiar with the concept of percentages. Unfortunately, as Figure 3 illustrates, the percentage of expected BMD value for age can be misleading. Since the mean BMD decreases with age, if we assume the spread of results remains constant across life, the decreasing denominator with ageing results in a wider range of percentage values representing the normal range. In other words, the lower limit of the reference range might be 60% of the mean in a 50-year-old person but could be 45% of the mean in a 75-year-old because the mean value is lower. This also causes problems with serial measurements in an individual. Consider the case of the individual in Figure 3 who at the age of 50 years is at the upper limit of the reference range with a BMD 120% of the mean value for age. If that individual loses bone at the average rate and remains at the upper limit of the reference range, at the age of 60 years their BMD will be 122% of expected for age and at the age of 70

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MEASUREMENT OF BONE MASS AND TURNOVER

years it will be 124% of expected, This creates the misleading impression that their BMD is increasing relative to the mean rather than remaining parallel. Figure 4 also shows how results from different measurement sites may be misleading if expressed as a percentage of the mean age-matched value. BMD, g/cm 2 1.4

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Figure 4. Each graph shows hypothetical bone mineral density (BMD) values for a 70-year-old individual at three m e a s u r e m e n t sites; the B M D is expressed as the absolute B M D and the reference range is shown as the shaded area 2SD either side of the mean. For a B M D value at the lower limit of the reference range in each case, i.e. 2SD below the m e a n for age, or on the 2.Sth percentile, the percentage of the expected value for age is 67% in the case of anteroposterior lumbar spine B M D , 50% for the lateral lumbar spine B M D , a site with a high coefficient of variation, and 82% for total body B M D , a m e a s u r e m e n t that has a m u c h smaller coefficient of variation.

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N. PEEL AND R. EASTELL

One way to overcome this problem is to express results in standard deviation (SD) units as a Z score. In most clinical situations the reference range is taken to be 2SD either side of the mean. This definition encompasses 95% of the population, assuming the data are normally distributed. If this is not the case, a transformation (e.g. logarithmic) may be needed to approxim a t e normality. Results may therefore be expressed in SD units as a Z score away from the m e a n value. As in the case of percentages, the Z score may be m a d e in comparison to age-matched or young normal controls, and it has the advantage that it may also be normalized for other variables such as bodyweight. A Z score in comparison to young normals is sometimes referred to as a T score. Z scores are not misleading in the same way as percentages, but as in the case of absolute B M D values have the disadvantage that they are not familiar to most clinicians and the significance of a result in terms of fracture risk is not immediately apparent. It has been shown that, for any m e a s u r e m e n t site, the risk of fracture at that site increases by two- to threefold with each SD decrease in B M D (Ross et al, 1991; Black et al, 1992). A n o t h e r way to overcome the problems associated with the use of percentages is to use percentiles. In this case, the reference range of 2SD either side of the m e a n represents the range between the 2.5th and the 97.5th percentiles. The advantages of this approach is that it is a familiar concept used in other areas of medicine, e.g. to express growth rate in children, and because it is a similar concept to a percentage it is easy to understand. The use of percentiles does not depend on a normal distribution of data and percentiles are not misleading, either in comparison to agematched controls or with serial measurements. The disadvantages of this m e t h o d are that it is not easy to m a k e a comparison with young normals as a percentile and that this approach is not being used at present by any of the densitometer manufacturers. The other difficulty in describing B M D results is that all the methods described here, apart from absolute B M D values, may change with each software update from the densitometer manufacturers. The implication of this is that in order to determine longitudinal change in an individual, in terms of percentages, Z scores or percentiles, it is necessary to analyse each scan using the latest software.

CLINICAL I N T E R P R E T A T I O N OF BMD M E A S U R E M E N T S Regardless of how the results are expressed, it is also important to discuss how they are interpreted. This may differ depending on the reason for the m e a s u r e m e n t . There are three reasons for measuring BMD: to determine the presence of absolute osteopenia, the degree of relative osteopenia, or to assess life-time fracture risk. Absolute osteopenia, or whether the B M D is below the reference range for a healthy young adult of the same sex and race, relates to an individual's current fracture risk. Relative osteopenia, or a B M D value lower than that expected for age, may be used to determine which individuals should be investigated for a secondary cause for osteoporosis. A c o m m o n reason for referral is oestrogen deficiency when the

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BMD result may influence whether a menopausal woman chooses to commence hormone replacement therapy (HRT) or the duration of treatment. As yet there are no clear recommendations for appropriate decision thresholds regarding treatment. A typical policy might be based on percentiles of the age-matched reference range. W o m e n whose BMD lies in the upper quartile of the reference range (above the 75th percentile) would be advised that H R T is not indicated for prevention of osteoporosis. Those women whose BMD is in the lowest quartile (below the 25th percentile), and who are at high risk of osteoporotic fracture, would be advised to take H R T . Those women whose BMD falls between these values are at moderate risk and the correct advice is unclear. In these women other considerations such as the presence of menopausal symptoms may influence the decision regarding H R T , and further investigation to estimate the rate of bone loss may be appropriate since H R T is likely to be less beneficial in the context of slow bone loss.

ESTIMATION OF LIFE-TIME FRACTURE RISK

While it is useful to assess current fracture risk, it would be far more useful to be able to predict the life-time risk of fracture. Current therapeutic approaches in osteoporosis are unable to replace significant quantities of bone once it has been lost, and it would be preferable to target preventive therapy to individuals identified as being at risk in the future. Any attempt to determine life-time fracture risk relates to the ability to predict BMD at some point in the future, since this is the major determinant of fracture risk. The relative contribution of peak bone mass and the subsequent rate of bone loss to later BMD is not established, and varies with time after peak bone mass is reached. In the early years after menopause, the peak bone mass is of major importance. Studies have demonstrated very high correlations between measurements made several years apart at this time of life, suggesting that differing rates of bone loss could explain only about 10-20% of the variance in bone mass. However, it has been shown that the biological variability of bone loss from the mid-shaft of the radius is large enough that by the age of 70 years the initial bone mass and the subsequent rate of loss contribute approximately equally to BMD (Hui et al, 1990). Mathematical models have been constructed to predict life-time fracture risk from initial BMD and age, taking into account variability in the rate of bone loss depending on initial BMD and estimated life expectancy (Melton et al, 1988). While such models may provide a useful projection in population terms, a more accurate prediction of the future fracture risk of an individual must take into account the individual's rate of bone loss. This can be determined from serial BMD measurements or an estimate may be made from measurement of the rate of bone turnover. Even basing such a prediction on data from an individual has limitations resulting from the inaccuracies of the methods involved and the fact that the rate of bone loss may not remain constant.

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SERIAL BMD M E A S U R E M E N T S TO PREDICT RATE OF BONE LOSS

The rate of bone loss in an individual may be determined from serial measurements of B M D , provided that the observed change is interpreted in the context of the error of the measurement. For a change in BMD to be significant, it must be greater than 2.8 times the precision error of the measurement calculated as a coefficient of variation. This represents the 95% confidence interval for the measurement, but it is important that the precision error relates to the population being studied. The published precision of B M D measurement techniques is often calculated from measurements made in a healthy population and underestimates the precision error in subjects with osteoporosis, in whom the mean B M D is lower. As an example, the precision error of lumbar spine B M D by D X A in an osteopenic population is in the order of 1%. A change in lumbar spine B M D must therefore exceed 2.8% to be significant. The average rate of bone loss is probably between 1% and 3% per year. It is therefore unlikely that a significant change in B M D will be measurable in less than i year and, to try to predict rates of loss, a considerably longer interval is necessary. Similarly, in the follow-up of patients receiving treatment for osteoporosis, ideally it is necessary to wait 2 years before making a further measurement to determine the efficacy of therapy. However, it may be difficult to maintain patient compliance for this period of time without providing evidence of benefit, and in practice a compromise is usually made to repeat the B M D measurement after 1 year.

ESTIMATION OF BONE LOSS FROM BIOCHEMICAL MARKERS OF BONE TURNOVER

Bone turnover may be assessedby three methods: (1) bone histomorphometry (Eriksen, 1986; Compston and Croucher, 1991); (2) calcium balance and calcium kinetic studies (Charles et al, 1985); and (3) biochemical markers of bone turnover. Biochemical markers have the advantage over the other techniques in that they enable the non-invasive estimation of bone turnover using relatively simple and rapid assays. Measurements may therefore be applied to large populations and repeated on a number of occasions. Any situation in which there is an imbalance between the processes of bone formation and resorption will result in a net increase or decrease of bone mass. This can occur in the context of either an increased or decreased rate of turnover. In simple terms, if the rate of bone turnover is increased and there is an imbalance in favour of resorption, the subsequent loss of bone mineral will be faster than in the case of decreased rate of turnover with an imbalance in favour of resorption. However, in the latter case, which occurs for instance in glucocorticoid therapy, it is possible that the rate of bone turnover may be inadequate to repair microfractures within the bone matrix. This could

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Table 3. Biochemical markers of bone turnover.

Formation markers

Resorption markers

Bone-specific isoenzyme of alkaline phosphatase Osteocalcin, bone Gla protein

Hydroxyproline

Procollagen type I C-terminal propeptide

Pyridinium cross-links of collagen, e.g. deoxypyridinoline Hydroxylysine glycosides, e.g. galactosyl hydroxylysine Tartrate-resistant acid phosphatase

result in a disproportionate decrease in bone strength for the actual decrease in bone mass. Postmenopausal osteoporosis is characterized by an increased rate of bone turnover. Table 3 summarizes the currently available markers of bone turnover that are described here. More comprehensive description of biochemical markers may be found in several recent reviews (Epstein, 1988; Delmas, 1992; Risteli and Risteli, 1993). Bone formation markers

Bone-specific alkaline phosphatase Alkaline phosphatase is an enzyme synthesized by a number of tissues. The bone-specific isoenzyme is produced by osteoblasts and localized in the matrix vesicles. Serum activity of this isoenzyme correlates with bone formation rates determined by bone histomorphometry (Eastell et al, 1988). Alkaline phosphatase molecules produced in bone, liver and kidney are all formed from an identical gene product and the three types differ only in their post-translational carbohydrate modifications. These differences enable the isoenzymes to be differentiated using methods such as electrophoresis and wheatgerm lectin precipitation (Sorensen, 1988). Immunoassays to the bone-specific isoenzyme are under development, but currently available assays are limited by cross-reactivity with the liver isoenzyme.

Osteocalcin (bone Gla-protein, BGP) This peptide is produced by osteoblasts during bone formation and incorporated into the bone matrix where it may have a role in mineralization. A small proportion, which is probably constant, of newly synthesized osteocalcin is not incorporated into the matrix and is released into serum where it may be measured by radioimmunoassay (Power and Fottrell, 1991; Garnero et al, 1992). Since intact osteocalcin is not released from the bone matrix on bone resorption, intact osteocalcin levels in serum reflect the bone formation rate, and correlate better with rates measured by bone histomorphometry than bone alkaline phosphatase (Eastell et al, 1988). However, there are limitations of this marker in some clinical situations, such as in patients with rheumatoid arthritis or in the presence of corticosteroids. There may be a direct suppressive effect on the production of osteocalcin by the osteoblast in this situation which does not reflect bone formation rates. Different assays

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vary in specificity for the intact peptide, and cross-reactivity with osteocalcin fragments may mean that some assays detect immunoreactive fragments derived from bone resorption. Osteocalcin is also very unstable, particularly in the presence of haemolysis, and serum samples should be frozen within 1 hour of collection. Long-term storage of samples should be at -70~

Procollagen type-I C-terminal propeptide (PICP) Type I collagen is the predominant bone collagen and is synthesized by osteoblasts as a precursor form, procollagen. This is subsequently cleaved into collagen and the carboxy- and amino-terminal propeptides (PICP and PINP). PICP can be measured in serum by radio-immunoassay (Melkko et al, 1990). However, type I collagen is not specific to bone, the other major source being from skin. Although this marker does reflect bone formation rates (Simon et al, 1984), it is less bone-specific than the other bone formation markers. Bone resorption markers

Hydroxyproline Urinary hydroxyproline has been used as a marker of bone resorption for a long time but is relatively non-specific and is now being superseded by newer markers. It is present not only in many types of collagen, where it stabilizes the triple helical structure, but is also produced as a breakdown product of the Clq component of complement. On release from the collagen matrix it is extensively metabolized, with only about 10% being excreted in the urine. It is also absorbed from gelatin-containing foods in the diet and fasting samples are therefore required (Gasser et al, 1979).

Pyridinium cross-links The pyridinium cross-links of collagen, pyridinoline (Pyd) and deoxypyridinoline (Dpd) are the maturation products of intermediate ketoamine cross-links between collagen fibrils. On breakdown of collagen, they are released and excreted in the urine in either the free or peptide-bound form. There are a number of advantages of the cross-links as markers of bone resorption over hydroxyproline. Although Pyd is the predominant cross' link in bone, being present in a ratio of 3-4 : 1 compared with Dpd, Dpd is essentially bone-specific since it is present in type I collagen of bone and dentine but not of skin (Eyre et al, 1984). The cross-links are unaffected by dietary collagen ingestion (Colwell et al, 1993) and do not appear to be metabolized. The urinary excretion of the cross-links has been validated as a marker of bone resorption rates, both against bone histomorphometry (Delmas et al, 1991) and against radiostrontium kinetics (Eastell et al, 1990). Cross-links may be measured by high-performance liquid chromatography and fluorescence spectroscopy following acid hydrolysis to convert the peptide-bound to the free form, and cellulose-column partition chroma-

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tography to remove interfering fluorescent compounds (Eyre et al, 1984; Black et al, 1988). Recent developments in the measurement of the crosslinks include description of an automated assay and the use of internal standards which enable single samples to be measured, thus halving the assay time (Pratt et al, 1992; Colwell et al, 1993). An enzyme-linked immunosorbent assay for the urinary free Pyd has recently been introduced. Once it has been validated, this will be an important advance if the crosslinks are to be used in routine clinical practice. Other developments in the measurement of the cross-links are assays to the cross-linked telopeptide regions of collagen that are released on collagen breakdown. Immunoassays for the carboxy-terminal telopeptide of type I collagen in serum and the amino-terminal telopeptide in urine are under evaluation (Hanson et al, 1992).

Hydroxylysine glycosides The urinary excretion of the hydroxylysine glycoside, [3-1-galactosyl hydroxylysine (GH) is probably a more specific marker of bone resorption than hydroxylysine, as there appears to be less effect of diet and it may undergo less metabolism. GH is the major form of the hydroxylysine glycosides in bone whereas c~-l,2-glucosyl galactosyl hydroxylysine (GGH) predominates in skin. GH may be measured by high-performance liquid chromatography and fluorescence spectroscopy in urine samples after reaction with dansyl chloride. It remains to be evaluated whether it has any advantages over the cross-links as a marker of bone resorption (Moro et al, 1984; 1988a; 1988b).

Tartrate-resistant acid phosphatase (TRAP) Serum acid phosphatase is derived from several sources such as bone, prostate and blood cells. The bone isoenzyme, thought to be the type Vb isoform, is resistant to tartrate, and may reflect the bone resorption rate. Current assays do not correlate well with other bone resorption markers, however, and this probably reflects poor specificity of the assays. Immunoassays for the type Vb isoform are under development and these may enable this to become a useful marker (Kraenzlin et al, 1990). CLINICAL INTERPRETATION OF B I O C H E M I C A L M A R K E R S OF BONE T U R N O V E R

The optimum use of these markers in clinical practice has yet to be established. In addition to the limitations of some of the individual markers, alluded to above, there are a number of problems common to all the markers. There appears to be considerable diurnal variation in the markers of resorption and, to a lesser extent, those of formation (Eastell et al, 1992). This seems to reflect diurnal changes in the processes of bone turnover, but differences in the magnitude of this diurnal variation between different

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markers may simply reflect differences in bone specificity. The implications Of this are that care needs to be taken over timing of sample collection, especially in the case of markers with a short half-life within the circulation, such as osteocalcin. In the case of urinary markers 24-h collections are preferable and, if 2-h or random samples are used, it is important that all samples are collected at the same time of day. All of the markers demonstrate a wide reference range with considerable overlap between healthy and diseased populations. This means that the markers cannot be used to diagnose osteoporosis and initial hopes that they could be used to differentiate fast from slow bone losers may be unrealistic. Probably the greatest potential of the biochemical markers lies in their use to identify change in rates of bone turnover, either during disease progression or in response to therapy, and possibly to predict which individuals are likely to show a good response to antiresorptive therapy. This will probably be best achieved using a combination of markers to measure changes in the balance between rates of formation and resorption. As in the case of BMD measurement, consideration must be given to the way in which results are expressed. Currently, most published studies using biochemical markers in serial studies describe change in terms of percentage of the initial value. This is misleading in that the percentage change will appear greater in those patients with the lowest initial values. Results also cannot be compared meaningfully as percentages between different markers since each has a different coefficient of variation and some do not demonstrate a normal distribution. A solution to this difficulty might be to use Z scores to report results for the biochemical markers, following logarithmic transformation if necessary. This approach would not only allow comparison between different markers within an individual but would also allow comparison of changes over time. A L G O R I T H M S TO PREDICT FUTURE F R A C T U R E RISK

Few attempts have yet been made to combine measurements of BMD together with biochemical estimates of bone turnover rate into an algorithm to predict bone mass at a later date (Blumsohn and Eastell, 1992). One such study used an equation based on four parameters of bone turnover: serum total alkaline phosphatase activity, fasting urinary calcium and hydroxyproline levels, and body-weight (Hansen et al, 1991). The bone loss over 12 years estimated from these parameters correlated with measured bone loss at the distal radius, with a 10% difference in bone mass between those predicted to be fast and slow bone losers. This study is encouraging, considering that the biochemical tests available at the base-line are all relatively non-specific for bone. The model has recently been updated to include serum osteocalcin in place of body-weight, with a small improvement in predictive ability over 24 months (Christiansen et al, 1990). Another study has shown that up to 58% of the variation in rates of bone loss from the distal radius over 4 years can be explained by an equation involving urinary pyridinoline and oestrogen excretion, together with body mass index (Mole

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et al, 1992). H o w e v e r , before such algorithms can be useful in clinical practice it m u s t be established w h e t h e r b o n e mass can be reliably p r e d i c t e d at the site of clinically i m p o r t a n t o s t e o p o r o t i c fractures, n a m e l y the spine a n d hip, a n d w h e t h e r these p r e d i c t i o n s r e m a i n valid over long periods.

SUMMARY B o n e mass is the most i m p o r t a n t d e t e r m i n a n t of fracture risk. C u r r e n t b o n e mass of a n i n d i v i d u a l will be d e t e r m i n e d by the p e a k b o n e mass achieved in early adult life a n d the s u b s e q u e n t d u r a t i o n a n d rate of b o n e loss. I n a t t e m p t i n g to predict an i n d i v i d u a l ' s f u t u r e risk of fracture it is t h e r e f o r e logical to a t t e m p t to assess both of these p a r a m e t e r s . Serial m e a s u r e m e n t s of b o n e m i n e r a l density a n d e s t i m a t i o n of the rate of b o n e t u r n o v e r m a y also be used to d e t e r m i n e the r e s p o n s e to t r e a t m e n t . I n this c h a p t e r we review the c u r r e n t l y available m e t h o d s of m e a s u r i n g B M D a n d b o n e t u r n o v e r , a n d discuss their place in the diagnosis a n d m a n a g e m e n t of osteoporosis.

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